TR2024-137

Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking


    •  Chang, H., Boularias, A., Jain, S., "Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking", 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024), October 2024.
      BibTeX TR2024-137 PDF
      • @inproceedings{Chang2024oct,
      • author = {Chang, Haonan and Boularias, Abdeslam and Jain, Siddarth}},
      • title = {Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking},
      • booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)},
      • year = 2024,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2024-137}
      • }
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  • Research Areas:

    Computer Vision, Robotics

Abstract:

Recent advancements in autonomous robotic assembly have shown promising results, especially in addressing the precision insertion challenge. However, achieving adaptability across diverse object categories and tasks often necessitates a learning phase that requires costly real-world data collection. Moreover, previous research often assumes either the rigid attachment of the inserted object to the robot’s end-effector or relies on precise calibration within structured environments. We propose a one-shot method for high-precision contact-rich manipulation assembly tasks, enabling a robot to perform insertions of new objects from randomly presented orientations using just a single demonstration image. Our method incorporates a hybrid framework that blends 6-DoF visual tracking- based iterative control and impedance control, facilitating high- precision tasks with real-time visual feedback. Importantly, our approach requires no pre-training and demonstrates resilience against uncertainties arising from camera pose calibration errors and disturbances in the object in-hand pose. We validate the effectiveness of the proposed framework through extensive experiments in real-world scenarios, encompassing various high-precision assembly tasks.